Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 1 of 18
Time line of redox events in aging
Nicolas Brandes1†, Heather Tienson1†, Antje Lindemann1, Victor Vitvitsky2,
Dana Reichmann1‡, Ruma Banerjee2, Ursula Jakob1,2*
1Department of Molecular, Cellular, and Developmental Biology, University of
Michigan, Ann Arbor, United States; 2Department of Biological Chemistry, University
of Michigan Medical School, Ann Arbor, United States
Abstract The precise roles that oxidants play in lifespan and aging are still unknown. Here, we
report the discovery that chronologically aging yeast cells undergo a sudden redox collapse, which
affects over 80% of identified thiol-containing proteins. We present evidence that this redox
collapse is not triggered by an increase in endogenous oxidants as would have been postulated by
the free radical theory of aging. Instead it appears to be instigated by a substantial drop in cellular
NADPH, which normally provides the electron source for maintaining cellular redox homeostasis.
This decrease in NADPH levels occurs very early during lifespan and sets into motion a cascade that
is predicted to down-regulate most cellular processes. Caloric restriction, a near-universal lifespan
extending measure, increases NADPH levels and delays each facet of the cascade. Our studies
reveal a time line of events leading up to the system-wide oxidation of the proteome days before
Most living animals undergo a physiological decline with age. Yet, despite decades of intense study,
no consensus has emerged regarding the primary cause of this decline. One leading hypothesis is the
free radical theory of aging, which postulates that aging is caused by an accumulation of oxidative
damage to cellular macromolecules (Harman, 1956). Many lines of correlative evidence support this
theory (Muller et al., 2007). However, while these studies confirm the general notion that oxidative
damage is associated with aging, recent studies in mice have generated conflicting results as few of
the genetic manipulations targeting conserved antioxidant genes showed the predicted effects on
lifespan (Perez et al., 2009). Hence, the jury is still out on the question of whether oxidative damage
is a cause of aging or simply a consequence (Salmon et al., 2010).
One obstacle in defining the role of oxidants in aging is our lack of knowledge of when, or even if,
reactive oxygen species (ROS) accumulation causes physiological alterations that are severe enough
to affect the lifespan of an organism and whether manipulation of the onset of oxidative stress will
alter lifespan. So far, the most commonly used read-out for oxidative protein damage involves
detection of protein carbonylation (Shacter et al., 1994; Levine, 2002). However, neither the extent
of carbonylation nor the specific effect(s) of carbonylation on protein activity are easily assessed. To
get a better handle on evaluating oxidative protein modifications, we developed a highly sensitive and
fully quantitative mass spectrometry-based redox technique (i.e., OxICAT) that allows us to determine
the in vivo oxidation status of hundreds of different protein thiols in organisms and to identify the
proteins affected (Leichert et al., 2008). We recently used OxICAT in Saccharomyces cerevisiae to
quantify the steady-state oxidation status of almost 400 different yeast protein thiols and identify
those proteins that contain peroxide and redox-sensitive cysteines (Brandes et al., 2011). We then
reasoned that by monitoring the exact oxidation status of these proteins during the chronological
†The first two authors
contributed equally to this work
‡Present address: Department
of Biological Chemistry, Hebrew
University of Jerusalem,
Competing interests: The
authors have declared that no
competing interests exist
Funding: See page 16
Received: 06 October 2012
Accepted: 08 December 2012
Published: 05 February 2013
Reviewing editor: Karsten Weis,
University of California-Berkeley,
Copyright Brandes et al. This
article is distributed under the
terms of the Creative Commons
Attribution License, which
permits unrestricted use and
redistribution provided that the
original author and source are
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 2 of 18
lifespan of yeast, we will obtain a spatial and temporal read-out of the prevailing oxidation conditions
during the aging process. We should also be able to uncover protein targets whose oxidative thiol
modifications might contribute to the physiological alterations that are observed in aging organisms
and might even be able to establish a clear correlation between onset and extent of oxidative stress
The chronological lifespan of S. cerevisiae represents a popular model system for analyzing aging
in postmitotic cells. Chronological lifespan is defined as the length of time that non-dividing cells
remain viable in a high metabolic state (Fabrizio and Longo, 2007; Fontana et al., 2010). In support
of the free radical theory of aging, chronological lifespan decreases in yeast strains lacking the oxidant
scavenging enzymes superoxide dismutase (SOD) or catalase (Longo et al., 1996) and increases when
glutathione or SOD levels are elevated (Harris et al., 2003). Also, caloric restriction, a nearly universal
measure to extend lifespan, has been shown to significantly increase chronological lifespan in yeast
(Fontana et al., 2010). Although the molecular mechanism by which caloric restriction extends lifespan
has not been elucidated, one unifying trait among calorically restricted organisms is a significantly
increased oxidative stress resistance (Barja, 2002).
In this study, we used chronologically aging S. cerevisiae to determine the onset, extent, and
targets of protein oxidation in postmitotic aging cells. By monitoring the thiol oxidation status of
almost 300 different protein thiols, we discovered that yeast cells undergo a global redox collapse that
eLife digest While most animals experience a physiological decline as they age, the underlying
cause of this decline is not fully understood. According to the free radical theory of aging, chemicals
known as reactive oxygen species build up in the body and then cause damage to various components
within cells, including DNA and proteins. These species, which include hydrogen peroxide and
peroxynitrite, can cause substantial oxidative damage. However, while there is definitely a
relationship between aging and reactive oxygen species, it remains possible that oxidative damage
is a byproduct of aging rather than the cause of it.
In the past researchers have measured the carbonylation of proteins (that is, the oxidation of
certain amino acids in proteins) as a proxy for damage caused by reactive oxygen species, but this
method has a number of shortcomings. More recently, it has become possible to quantify the
oxidation state of cysteine, an amino acid that contains sulfur, in proteins using a technique based
on mass spectrometry. Building on previous work in which they used this technique to measure the
oxidation state of 300 proteins in vivo in the yeast Saccharomyces cerevisiae, Brandes et al. have
now determined how the oxidation state of these proteins changes over the lifespan of
S. cerevisiae, which is a popular model system for analyzing aging in cells that are in a high metabolic
state but are no longer dividing. This made it possible to identify protein targets that might—as a
result of changes in their oxidation state caused by reactive oxygen species—contribute to the
physiological alterations observed in aging organisms. It was also possible to establish a clear
connection between the onset and extent of oxidative stress and lifespan.
Brandes et al. discovered that several days before the yeast cells died, they underwent a sudden
and global ‘redox collapse’ in which ∼80% of the 300 proteins being studied experienced an
increase in their oxidation state (i.e., they lost electrons). This event was preceded by a large drop
in the level of NADPH, a coenzyme that, by being a source of electrons, helps to counterbalance
the removal of electrons by reactive oxygen species within cells. The drop in the concentration of
NADPH occurred very early in the life cycle of the yeast, and set in motion a series of events that
down-regulated most cellular processes. Intriguingly, these findings are consistent with the effect of
caloric restriction, a condition that is known to extend the lifespan of animals. Caloric restriction
increases cellular NADPH and delays the down-regulation of cellular processes.
Brandes et al. propose that the underlying cause of aging is not the accumulation of reactive
oxygen species: rather, these results suggest that aging is caused by a sudden and substantial
decrease in available NADPH, which means that cells cannot maintain a stable oxidation state. If
borne out by further work, these findings could have a significant impact on how we think about the
aging process, and could require researchers to rethink how they study aging.
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 3 of 18
leads to massive thiol oxidation in almost 80% of identified proteins several days prior to cell death.
Cluster analysis revealed that this general protein oxidation is preceded by the oxidation of a subset
of conserved proteins, one of which is NADPH-dependent thioredoxin reductase, a key enzyme in
maintaining redox homeostasis. Redox metabolite and NADPH studies suggested that protein
oxidation is triggered by a decrease in cellular NADPH concentration. Consistent with this hypothesis,
caloric restriction delayed NADPH decrease, early protein oxidation, global redox collapse, and cell
death. Our results suggest that the decrease in cellular NADPH levels initiates oxidation of the cellular
redox machinery and triggers system-wide oxidation events, which significantly precede cell death.
Using OxICAT to monitor the in vivo redox status of proteins during
the chronological lifespan of yeast
Chronological lifespan measurements of S. cerevisiae wild-type and mutant strains suggested that
ROS might affect and potentially even determine the postmitotic lifespan of yeast (Longo et al., 1997;
Fabrizio and Longo, 2007). We therefore decided to apply the quantitative redox proteomic
technique OxICAT to monitor the redox status of our previously identified yeast protein thiols during
the chronological lifespan of this organism. OxICAT is based on the differential modification of in vivo
reduced and in vivo oxidized cysteine thiols, respectively with isotopically light 12C and isotopically
heavy 13C versions of the isotope-coded affinity tag (ICAT) thiol alkylating reagent (for scheme see
Figure 1—figure supplement 1A). This differential thiol trapping with ICAT is followed by a tryptic
digest of the proteins contained in the cell lysate and the purification of all ICAT-labeled peptides
using an affinity tag. Liquid chromatography combined with mass spectrometry (MS) and MS/MS
analysis is used to separate and identify the ICAT-labeled peptides, and to quantify the ratio of in vivo
reduced to oxidized protein thiols in individual peptides. Because this ratio is unaffected by changes
in relative protein amounts, OxICAT is uniquely suited to simultaneously monitor changes in the thiol
oxidation status of hundreds of proteins over time.
We had previously identified and quantified the steady-state oxidation level of almost 400 thiol-
containing peptides in about 290 different yeast proteins localized to various cellular and subcellular
compartments (Brandes et al., 2011). We now reasoned that by simultaneously monitoring the thiol
oxidation status of all these proteins during postmitotic aging, we should be able to track potential
redox changes and identify affected proteins and pathways, provided that oxidant levels and redox
conditions changed significantly during the lifespan of the organism. Moreover, by cultivating yeast
cells under different conditions, including conditions such as caloric restriction, which has previously
been shown to alter chronological lifespan (Fontana et al., 2010), we should be able to reveal any
correlation between onset and extent of oxidative stress and the lifespan of yeast.
We therefore cultivated the wild-type yeast strain DB746 under three different conditions:
standard, caloric restriction, or with a water ‘starvation’ diet. Under standard conditions, 2% glucose
SCD media is used and DB746 cells maintain their high metabolic, postdiauxic state until they die
(mean lifespan ∼7 days) (Fabrizio and Longo, 2007) (Figure 1A). Under caloric restriction (CR), 0.5%
glucose SCD media is used, which increases respiration, promotes higher oxidative stress resistance,
and extends lifespan (mean lifespan ∼11 days) (Figure 1A) (Fabrizio and Longo, 2003). With the starvation
diet, cells are provided 2% glucose SCD media for 2 days followed by incubation in water. Under these
conditions, yeast cells switch to a hypometabolic state (stationary phase) and show dramatically
increased lifespan (mean lifespan > 15 days) (Figure 1A) (Fabrizio et al., 2003). We monitored growth
for the first 24 hr (Figure 1—figure supplement 1B), and took samples for our OxICAT analysis at
24-hr intervals starting during exponential growth (day 0) and continuing until 10–20% of cells were
dead (day 4 in standard media, day 7 in caloric restriction media) or up to day 10 in water.
To initially determine whether and when ROS levels change during yeast chronological aging, we
analyzed the thiol oxidation status of glyceraldehyde-3-P dehydrogenase (GapDH, TDH) as this protein
has some of the most redox-sensitive cysteines in yeast and other organisms (Brandes et al., 2011).
GapDH contains two redox-sensitive cysteines (the active site Cys150 and the nearby Cys154), and
both of these are found in the same tryptic peptide (GapDH144–160). We previously suggested that these
cysteines form an intramolecular disulfide bond during peroxide stress in vivo (Brandes et al., 2011).
During the first 2 days of cultivation under either standard or caloric restriction conditions, we
found that the GapDH144–160 peptide was predominantly labeled with two light ICAT molecule and less
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 4 of 18
Figure 1. The active site cysteines of GAPDH become increasingly oxidized during the chronological lifespan of
yeast. Chronological lifespan of S. cerevisiae strain DBY746 was monitored under either 2% glucose standard
conditions (closed circles) or 0.5% glucose caloric restriction (CR) conditions (closed squares). Alternatively, cells
were cultivated under 2% glucose standard conditions for two days, washed and resuspended in water to induce
hypometabolic cultivation conditions (open circles). Cell aliquots were taken at the indicated time points and
(A) viability was determined using propidium iodide (PI) staining or (B–D) the thiol oxidation status of Cys150/Cys154
in GapDH was quantified by differential thiol trapping using OxICAT. Representative MS spectra of the differentially
ICAT-labeled GapDH144–160 peptide containing Cys150 and Cys154 are shown in panels C and D. The mass peak at
m/z 2161.13 corresponds to the reduced GapDH144–160 peptide in which both cysteines are labeled with light ICAT.
The 18 Da heavier mass peak at m/z 2179.13 corresponds to the oxidized GapDH144–160 peptide in which both
cysteines are labeled with heavy ICAT.
The following source data and figure supplements are available for figure 1:
Source data 1. Average oxidation status with standard deviation of protein thiols identified in at least three
biological replicates under each cultivation condition.
Figure supplement 1. (A) Schematic overview of the OxICAT procedure.
than 30% of the two cysteines were calculated to be oxidized (Figures 1B–D). However, within the
next 24 hr (i.e., day 3) of cultivation under standard conditions, about 70% of the GapDH peptide was
labeled with two heavy ICAT molecules, indicating that both cysteines were oxidized (Figure 1C,
compare red and blue trace). This extent of oxidation is very similar to that observed in yeast cells
treated with 0.5 mM H2O2 for 15 min (Brandes et al., 2011). On day 4 under standard conditions, over
80% of all GapDH molecules were oxidized, indicating that by that time, glycolysis is dramatically
reduced. In contrast, the oxidation status of GapDH from yeast cells cultivated under caloric restriction
conditions remained low for the first 4 days of cultivation (Figures 1B,D). Then, however, significant
oxidation occurred (also within a 24-hr time window), with over 70% of all GapDH molecules affected
by day 5 and almost 90% affected by day 7 (Figure 1D, purple trace and black trace, respectively).
Yeast cells cultivated in standard media for 2 days and then switched into water showed no significant
increase in GapDH oxidation over the time span that was monitored by OxICAT (Figure 1B, open
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 5 of 18
circles and Figure 1—Source data 1), suggesting that under hypometabolic conditions, cells maintain
GapDH in its reduced and active state over extended periods of time.
Oxidation of the thiol redox proteome: a global and early event in the
chronological lifespan of yeast
To determine whether the observed thiol oxidation is restricted to a subset of particularly redox-
sensitive proteins or affects a wider range of yeast proteins, we analyzed the redox status of all of our
previously identified protein thiols during the chronological lifespan. We reproducibly identified 286 of
these protein thiols in all samples taken under standard 2% glucose conditions (i.e., all four replicates
at five different time points) (Figure 1—Source data 1). Most of these protein thiols were also
identified in the four replicates and seven time points taken from cultures cultivated under caloric
restriction conditions (i.e., 263 peptides), and 100 of these peptides were reproducibly identified
under hypometabolic water starvation conditions as well (Figure 1—Source data 1). We discovered
that the majority of our identified protein thiols found in standard and caloric restriction conditions
followed an oxidation pattern similar to that of GapDH’s active site cysteines (Figure 2A). The protein
thiols were largely reduced (Figure 2A, blue) for the first 48 hr post log phase (i.e., day 0) under standard
conditions or for the first 96 hr post log phase under caloric restriction conditions, and then became
suddenly oxidized within a 24-hr period (Figure 2A, red). After one more day of cultivation, the majority
of these protein thiols were then oxidized to over 80% (Figure 2A and Figure 1—Source data 1).
Shifting cells to water at day 2 of cultivation in 2% glucose SCD media prevented this sudden onset of
oxidation, and proteins showed only a minor increase in their thiol oxidation state, which persisted
until at least day 10 (Figure 2A and Figure 1—Source data 1).
Cellular processes affected by the redox collapse
Based on the large number of proteins that are affected by the apparent redox collapse in yeast cells,
it is not surprising that many of the identified proteins are involved in central physiological processes.
For instance, we found over 40 oxidation-sensitive proteins that play crucial roles in protein translation,
including 27 different thiol-containing 40S, 60S, and 54S ribosomal proteins, several translation
initiation (e.g., TIF11, GCD1) and elongation factors (e.g., EFT2, TEF1, TEF3), translational activators
(e.g., GCN1), and numerous tRNA synthetases (e.g., MES1, KRS1, VAS1). Oxidation of these proteins
most likely affects the rate and extent of protein synthesis in chronologically aging yeast cells.
Moreover, we found countless metabolic enzymes, including ACO1, PGK1, IDP1, PDC1, and TPI1 to
become oxidized, likely affecting processes ranging from the Krebs cycle and the pentose phosphate
pathway to fatty acid and amino acid synthesis. Also, numerous oxidation-sensitive proteins that we
identified are known to be involved in maintaining protein homeostasis, including chaperones (e.g., YDJ1,
HSP78, SSA1/2, SSB1/2, SSE1/2, SSZ1), prolyl isomerases (e.g., FPR1/2, CPR1, 6), components of the
proteasome complex (e.g., PRE10, PUP2), and ubiquitination machinery (e.g., UBC4), or serve as part
of the cellular antioxidant response (e.g., PRDX, thioredoxin reductase1/2) (Figure 1—Source data 1).
Many of these proteins have previously been found to contain redox-sensitive cysteines (Lindahl et al.,
2011). In fact, of the 290 different protein thiols that we monitored in our study, over 33% have been
confirmed to be redox-sensitive in yeast or other organisms (Figure 1—Source data 1). Moreover, an
additional 20% of our identified cysteines are localized to proteins that have been found to contain
redox-sensitive cysteines but whose redox-sensitive cysteines have not yet been fully identified. These
percentages were obtained by comparing our list of aging-oxidized protein thiols with the recently
published RedoxDB database, which compiled and manually curated over 2100 proteins with over
2300 redox-sensitive cysteines from different eukaryotic organisms (Sun et al., 2012). The high degree
of overlap between our identifications and the list of previously identified redox-sensitive proteins
in eukaryotes makes us confident about the specificity of our method. Our finding that over 80% of
an unbiased population of thiol-containing yeast proteins have the capacity to become significantly
oxidized under physiologically relevant growth conditions (Figure 1—Source data 1) suggests that
reversible cysteine oxidation, such as that detected with our OxICAT method, is a much more wide-
spread event than previously anticipated.
Despite the limited supply of nutrients in the stationary phase, oxygen consumption measurements
indicate that chronologically aging yeast cells are metabolically active in this phase (Fabrizio et al.,
2003; Fabrizio and Longo, 2003). Consistent with earlier ATP measurements conducted in chrono-
logically aging yeast cells (Goldberg et al., 2009), we found that intracellular ATP is indeed maintained
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 6 of 18
at levels equivalent to or above those present
during exponential growth for up to 5 days when
cultivated under standard postmitotic growth con-
ditions and for at least 7 days under caloric restric-
tion conditions (Figure 2B). These results
demonstrate that chronologically aging yeast
cells are not starving and are able to maintain
their energy resources and survive for extended
periods of times despite (or possibly even because
of) a heavily oxidized proteome.
Protein cluster analysis reveals
distinct waves of protein oxidation
Analysis of the kinetics of protein thiol oxidation
revealed that the majority of protein thiols in
yeast follow the trend observed for GapDH oxi-
dation: the thiol oxidation state is low for the
initial 2 days of cultivation then suddenly increases
by day 3 in standard media or by day 5 in caloric
restriction media. In addition, however, we noticed
several protein thiols whose oxidation appeared to
precede this global wave of oxidation by 24–48 hr
(Figure 2A). To investigate the significance of
this finding in detail, we clustered all identified
protein thiols according to their oxidation kinetics.
This cluster analysis is based on a k-means with
Euclidean distance algorithm (Saeed et al.,
2006). More than 95% of our identified protein
thiols clustered into one of seven distinct oxidation
clusters (named A–G) and most protein thiols
maintained their cluster assignment independent
of the cultivation condition (standard or caloric
restriction media) (Figure 3 and Figure 1—
Source data 1). Clusters A–C contained the
majority of our identified peptides and included
all those thiol groups that revealed a sudden
onset of oxidation by either day 3 in standard
media or day 5 in caloric restriction media. The
peptides only differed in their extent of oxidation
within the first 24 hr after onset of oxidation
(cluster A: >50% oxidation; cluster B: <50% oxida-
tion) or in their initial oxidation level (clusters A and
B: <20% oxidation; cluster C: >40% oxidation).
About 10% of identified peptides preceded this
general oxidation trend by 24–48 hr (Figure 3,
clusters D and E and Table 1). These peptides
showed significantly higher oxidation levels at
either day 1 (Figure 3, cluster D) or day 2 (Figure 3,
cluster E) compared to their oxidation states at
day 0. Importantly, most of these protein thiols
that were subject to early oxidation under one
condition were found to be early oxidation tar-
gets under the other cultivation condition as well. These peptides are of particular interest because
their oxidation may not just serve as an early warning of age-induced changes in the oxidative
status of cells, but might induce changes in their activity, which are involved in controlling or trig-
gering the oxidation of proteins in general. Only about 15% of the identified cysteine-containing
Figure 2. The redox homeostasis collapses early in
postmitotic yeast. (A) DBY746 cells were grown with initial
glucose concentrations of either 2% (standard) or 0.5%
(caloric restriction). At defined time points, samples were
taken for OxICAT analysis (see Figure 1, legend). To
determine the thiol oxidation status of cells under
hypometabolic conditions, cells were cultivated in
standard media for 2 days, washed, then shifted to water
prior to taking samples for OxICAT analysis. Each
identified peptide is depicted as a bar colored according
to its in vivo oxidation state from 0% (blue) to 100% (red)
(Figure 1—Source data 1). Peptides are organized by
their oxidation pattern in standard conditions. The color
presentation was done by Matlab. (B) Cells were cultivated
under standard (filled circles) or caloric restriction (open
squares) conditions. Cell aliquots were taken at the
indicated time points and total cellular ATP levels were
determined as described in ‘Material and methods’.
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 7 of 18
yeast peptides remained reduced (Figure 3, cluster
F) or stayed oxidized (Figure 3, cluster G) throughout
the course of the incubation (Figure 1—Source
Analysis of the subcellular distribution of the
proteins in the individual clusters did not reveal any
significant correlation between the location of the
proteins and their oxidation pattern (apart from
the expected accumulation of proteins of the
endoplasmic reticulum and secreted proteins in
cluster G) and reflected well the general subcellular
distribution of all identified proteins. To begin to
understand what specifies the cluster behavior of
the individual protein thiols, we performed a bio-
informatic analysis of the identified cysteine thiols.
In-depth analysis of the cysteine’s pKa-values or the
localization of the respective cysteine residues
within the proteins (e.g., surface exposed vs buried)
was unfortunately hampered by the limited number
of available protein structures (Brandes et al.,
2011). We thus performed a sequence analysis of
the 10 amino acids surrounding each identified
thiol group. To increase our sample size, we com-
bined clusters with similar oxidation trends and
initial oxidation levels (e.g., cluster A with cluster B,
cluster D with cluster E). The most noticeable dif-
ference among the thiol groups in the individual
clusters was that those cysteine thiols that became
oxidized early (clusters D and E) as well as protein
thiols with high steady-state levels of oxidation
during exponential growth (clusters C and G) had a
significant (p<0.05) accumulation of additional
cysteines in close proximity (Figure 4A, B). In
contrast, those protein thiols that stayed reduced
(cluster F) or were initially reduced and followed
the general oxidation trend (clusters A and B)
almost completely lacked the presence of nearby
additional cysteines. Chi-square-analysis confirmed
the significance of this finding and excluded the
dominance of any other amino acid type apart
from cysteine in close vicinity of the identified thiol
(Table 2A,B). These results suggest that the early
oxidation of a subset of yeast proteins is likely
triggered by a more oxidizing redox environment,
which causes those protein thiols that can undergo
stabilizing disulfide bonds with nearby cysteines to
accumulate in their oxidized state. One alternative
explanation, that a sudden surge in ROS, such as
peroxide, causes oxidation of a group of particularly
ROS-sensitive proteins, appears less likely as only a
few of our previously identified peroxide-sensitive
cysteines and none of our most peroxide-sensitive
peptides (i.e., GapDH) were found among the
group of early oxidation targets (Table 1). It also
remains to be seen what makes the about 8%
protein thiols in cluster F so resistant to protein
Figure 3. Cluster analysis of identified peptides
reveals early oxidation targets. All identified peptides
in cultures cultivated under standard or calorically
restricted conditions were clustered using the
k-means (Euclidean distance) clustering algorithm.
Each peptide is displayed by a black line; the red line
represents the average of the cluster. Over 70% of
peptides fall into clusters A–C. Cluster A: all peptides
with less than 30% thiol oxidation during log phase
and an increase in oxidation to more than 50% on day
3 (day 5 under caloric restriction conditions) of
cultivation; Cluster B: all peptides with less than 30%
thiol oxidation during log phase and an increase in
oxidation more than 50% on day 4 (day 6 under caloric
restriction conditions) of cultivation. Cluster C: all
peptides with ∼50% thiol oxidation during log phase
and a significant increase in oxidation on day 3
(day 5 under caloric restriction conditions) of
cultivation. Cluster D: all peptides that show an at
least 1.5-fold increase in thiol oxidation beginning on
day 1 (day 3 under caloric restriction conditions) of
cultivation. Cluster E: all peptides that show an at
least 1.5-fold increase in thiol oxidation beginning on
day 2 (day 4 under caloric restriction conditions) of
cultivation. Peptides in Clusters F and G remain
reduced or oxidized, respectively. The majority of
peptides identified under standard or calorically
restricted conditions fall into the same clusters (see
Figure 1—Source data 1 for details). Peptides in
cluster D or E are listed in Table 1.
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 8 of 18
Table 1. Early oxidation targets in yeast
Gene (Cys) ProteinLoc.
2% glucose (standard)
0.5% glucose (CR)
T-complex protein 1 subunit deltaC
122458 87861214 1311 3972 82
13 13 31 7174nd
Cell division control protein 48ER, C
122955 7593 13 151428626890
T-complex protein 1 subunit thetaC
47 4077 76 89nd
33 33 657782 34 3942 447380 86
Ubiquitin-conjugating enzyme E2 4N
19 23 487081 201522 24 49 73 88
UPF0587 proteinC, N
1522 49 7986 1411 12 48 5674 81
Homologue of DnaJC
46 4682 8975 454451 70738388
23 346486 82 20213161788098
Uncharacterized GTP-binding proteinC
171246918320 1022 29537888
Polyamine N-acetyltransferase 1C
2636 534861 1815 25 5261 7183
18235791 94 1214 2623778088
60S protein L10C
15 15 31 73 89 21172823598090
60S protein L42C
40S protein S11C
1817 37 778114 1727 2536 8386
40S protein S22-BC
139 34627232 2936 3241 7279
22 23 55 66 79 20191743657181
Isocitrate dehydrogenase 1M
181941 6185 1618322549 81 80
2-oxoglutarate dehydrogenase E1M
2521 495784 1818 19 16575470
Fatty acid synthase subunit alphaC, M
2216 3062861481559 81 8772
17 3847809116 183044 5570 84
Nuclear fusion protein FUS2N
18 33 5768809 18 12 2031 6491
Vacuolar aminopeptidase 1V
19 38458386 253527 223961 81
Pyruvate carboxylase 2C
1128 46 81 93 13 11 22 47667781
Elongation factor 1-alphaC
133840 62 701830 17 26365768
2622 28 70812422 2126287287
*Peroxide sensitive (Brandes et al. 2011).
†Follows the general oxidation pattern.
All cluster D and E proteins thiols whose oxidation kinetics significantly preceded the general oxidation trend are listed. Thiol oxidation states, which are
at least 2-fold higher as compared to day 0 or at least 1.5 fold higher as compared to day 0 and exceeding a total oxidation of 60% are shaded. Standard
deviations can be found in Figure 1—Source data 1.
oxidation, as it is conceivable that some of these proteins might play a role in promoting longevity.
Analysis of the nature of these proteins, which are listed in Figure 1—Source data 1, did not reveal
any striking trends in regards to their functions or subcellular localizations. We assume that their
oxidation resistance is based on potentially unusual structural features influencing the reactivity of the
cysteine thiol, such as an abnormal pKa-value or a very buried nature. However, at this point, we lack
sufficient structural information on this group of proteins to draw any firm conclusions why some of
their cysteines are so oxidation resistant.
Thioredoxin reductase: an early oxidation target in yeast
Oxidation of at least 28 proteins significantly preceded the general oxidation of proteins under
standard or caloric restriction conditions (Figure 3, clusters D and E and Table 1). Of these
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 9 of 18
early-oxidized proteins, 20 had oxidation states of more than 45% at day 2 of cultivation, which was
1.5- to 3.8-fold higher than their oxidation status during exponential growth. One of these early oxidation
targets is the highly conserved enzyme thioredoxin reductase, the key component of the thioredoxin
system. Although we cannot exclude that oxidation of any one of the other early oxidation targets
Figure 4. Comparison of sequence conservation between individual protein clusters. Analysis of sequence conservation (A) and amino acid type (B) in
sequence fragments spanning five amino acids up- and downstream of the thiol group whose oxidation status was determined by OxICAT. Peptide
sequences from clusters A and B were combined as were sequences from clusters D and E. (A) Sequence logos of the 11-amino acid peptides were
aligned at the position of the identified cysteine. The color code corresponds to the amino acid type, with Cys shown in black, negatively charged amino
acids shown in red, positively charged amino acids shown in blue, non-polar amino acids shown in grey, aromatic amino acids shown in yellow, and
polar amino acids shown in green. The residue order in each column corresponds to the relative occurrence of the residue in the specific position. The
height of the amino acid corresponds to its relative frequency at the specific position. The logos were created using WebLogo (Crooks et al., 2004).
(B) The relative amino acid occurrence, excluding the OxICAT-identified cysteine, in the sequence fragments was analyzed. As in (A), the amino acids
were grouped according to their characteristics and the occurrence of the amino acid type was normalized to the distribution of the same amino acid
type in the entire library of sequence fragments. A value of 1 indicates that the occurrence of a specific amino acid is identical to the occurrence of this
group of amino acids in the total sequence library.
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 10 of 18
directly or indirectly affects or even controls S. cerevisiae lifespan, we decided to focus our subsequent
studies on thioredoxin reductase, as this enzyme is the central player in maintaining cellular redox
homeostasis. Loss of thioredoxin reductase activity has been shown to cause widespread protein
oxidation (Holmgren and Lu, 2010). We found that the oxidation of thioredoxin reductase’s two
active site cysteines, which are arranged in the prototypical C-X-X-C motif, raised sharply by about
twofold to 65% at least 24 hr before the general redox collapse began (Figure 5, compare blue and
red trace) and was close to 80% at day 3 of cultivation under standard conditions (Figure 5 and Table 1).
The same trend was observed under caloric restriction: although oxidation of thioredoxin reductase
was delayed by 48 hr relative to what was seen under standard conditions, it again preceded the
general redox collapse by about 24 hr (Table 1). Note that a shift to extreme caloric restriction (water)
partially reversed the early oxidation of thioredoxin reductase that was noticeable at day 2 of
cultivation (Figure 5). Within 24 hr upon shift into water, we observed a significant reduction in
thioredoxin reductase’s oxidation status, which reached levels that were only slightly above the initial
oxidation levels of thioredoxin reductase in exponentially growing yeast cells (Figure 5). These low
levels of oxidation were then maintained for the remainder of the experiment, consistent with our
previous observations that yeast proteins do not become significantly oxidized upon shift into water
during the time period tested. These results suggest that early interventions restore the activity of
thioredoxin reductase and also prevent the collapse of cellular redox homeostasis.
To further elucidate what role if any thioredoxin reductase plays in postmitotic lifespan, we decided
to generate yeast mutants lacking either the cytosolic (thioredoxin reductase 1) or the mitochondrial
(thioredoxin reductase 2) form of thioredoxin reductase in our DBY746 strain. We found that while
Δtrr2 mutants grew like wild-type yeast cells and had a wild-type like chronological lifespan, deletion
of the cytosolic TRR1 homologue (Δtrr1) caused severe growth defects and a significantly shortened
lifespan (Figure 5—figure supplement 1). Moreover, we observed the generation of healthy-looking
Δtrr1 suppressors with very high frequency. In fact, cultivation of Δtrr1 deletion mutants without the
potential generation of suppressors was only possible when the medium was supplemented with
cysteine, presumably to maintain proteins in their reduced state. This cysteine requirement, however,
made the investigation of the oxidation status of proteins in Δtrr1 strains very difficult, and the
interpretation of the effects of a ttr1 deletion on lifespan very challenging. Organisms lacking
Table 2. Chi-square analysis of amino acid type distribution in sequence fragments containing the
identified thiol group according to clusters
Table 2A. Amino acid distribution was analyzed in the sequence fragments spanning five amino acids up- and
downstream of the cysteine thiol (Figure 4), whose oxidation status was determined by OxICAT. The identified
cysteine thiol was not included in the analysis. Table 2B. Chi-square analysis of the amino acid type distribution in the
same sequence fragments analyzed in Table 2A removing any cysteines from our analysis. p-values obtained from the
chi-square analysis of distribution of different amino acid types, positively and negatively charged, polar, non-polar,
aromatic amino acids and cysteines (for Table 2A only) in clusters A through G (Figure 3). Degrees of freedom are 5
(Table 2A) and 4 (Table 2B), respectively. Significantly different distributions are shown in bold (p<0.05, a = 0.95).
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 11 of 18
thioredoxin reductase have previously been shown to be either severely compromised in growth or
non-viable (Holmgren and Lu, 2010). This illustrates the essential role that maintenance of the cellular
redox homeostasis plays in organisms and explains why directly investigating the role of thioredoxin
reductase in the lifespan has remained great challenge.
Depletion of cellular NADPH levels: the trigger for early protein
The NADPH-dependent thioredoxin system is one of two highly conserved multi-enzyme systems that
contribute to the maintenance of cellular redox homeostasis in most pro- and eukaryotic organisms.
The other system consists of NADPH-dependent glutathione reductase, several small glutaredoxins,
and the cysteine-containing tripeptide glutathione (GSH), which together with its oxidized counterpart
GSSG determines the cellular redox potential (Martensson and Meister, 1989; Merad-Boudia et al.,
1998). To investigate potential changes in the redox potential of postmitotic yeast cells cultivated in
standard or caloric restriction media, we took samples during chronological aging of DBY746 yeast
cells and determined total GSH and GSSG concentrations at the same time points at which we
previously analyzed the thiol oxidation states. As shown in Figure 6A, we found that during exponential
growth, the glutathione redox potential did not differ between yeast cells cultivated in standard or
caloric restriction conditions. However, by day 1 of cultivation in standard conditions, yeast cells
Figure 5. Early oxidation of thioredoxin reductase is reversible in vivo. Yeast strain DBY746 was cultivated under
standard conditions for 2 days (lower panel). Then, the culture was split and either continued to be cultivated in
standard media (upper left panel) or shifted to water (upper right panel) to induce hypometabolic cultivation
conditions. Representative MS spectra of the differentially ICAT-labeled thioredoxin reductase peptides containing
the two active site cysteines Cy142/Cys145 before and after the shift are shown. Within 24 hr after shifting cultures
to hypometabolic cultivation conditions (day 3), the increased thiol oxidation of thioredoxin reductase’s active site
cysteines observed at day 2 is largely reversed.
The following figure supplements are available for figure 5:
Figure supplement 1. Role of thioredoxin reductase in the chronological lifespan of yeast.
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 12 of 18
showed an at least 15 mV increase in their overall
redox potential, which induces a significant
shift in the thiol/disulfide or thiol/sulfenic acid
equilibrium of proteins that are in equilibrium
with the GSH/GSSG couple. In contrast, yeast
cells cultivated under caloric restriction con-
ditions experienced a much smaller initial
increase in the cellular redox potential. This
result agrees with previous studies that revealed
a more oxidizing environment for cells in stand-
ard media as compared to caloric restriction
media (Magherini et al., 2009). Importantly,
cells cultivated in caloric restriction media
showed a 48-hr delay to reach the same redox
potential observed in cells cultivated in standard
media (Figure 6A). This delay is consistent
with our previously observed 48-hr delay in
protein oxidation in yeast cells cultivated in
caloric restriction media as opposed to stand-
Both thioredoxin reductase and glutathione
reductase draw their reducing power from
NADPH, making the oxidation status of these
systems ultimately dependent on cellular
NADPH and NADP+ levels. We therefore
measured the levels of NADPH and NADP+ in
yeast samples cultivated under both standard
and caloric restriction conditions. We found that
exponentially growing yeast cells have very
similar levels of NADPH and NADP+ independent
of their initial glucose availability, and that
these levels increased over the next 12 hr under
both cultivation conditions (Figure 6B). In this
time frame, yeast cells undergo a diauxic
shift from glucose-driven fermentation to
ethanol-driven respiration. Cells induce NADH
kinases such as UTR1 and POS5, glucose-6-
phosphate dehydrogenase (ZWF1), and the
cytosolic NADPH-dependent isocitrate dehydro-
genase (Idp2) to increase NADPH production
and regeneration (Gasch et al., 2000). In
cells cultivated under standard conditions,
the intracellular levels of NADPH then rapidly
decreased over the next 24-hr time period. In
contrast, in cells cultivated under caloric
restriction conditions, NADPH levels decreased
with much slower rates and reached concentra-
tions comparable to those observed in standard media with about a 48-hr delay (Figure 6B). This drop
in intracellular NADPH levels coincided well with the initial oxidation of thioredoxin reductase and the
alteration in the cellular redox potential. It is unclear why yeast cells grown under standard conditions
show increased levels of both NADP+ and NADPH at day 4 of cultivation in standard media (Figure 6B).
It is conceivable that cells cannibalize and hence may take up metabolites from surrounding dying
cells. Alternatively, oxidation and potential inactivation of NADPH-utilizing enzymes might serve as
negative feedback loop and lead to the observed increase in NADPH levels. In summary, these results
suggest that early changes in cellular NADPH levels might serve as trigger for the initial oxidation of
thioredoxin reductase and changes in the cellular redox potential, which subsequently leads to the
Figure 6. Loss of cellular NADPH might trigger redox
collapse. Strain DBY746 was cultivated under standard
(full circles) or caloric restriction (open squares) conditions
as described in Figure 1. At the time points indicated,
samples were taken for (A) whole cell analysis of GSH and
GSSG levels or (B) NADPH/NADP+ measurements. The
glutathione redox potential EGSH was calculated using the
Nernst equation. Data points are the average of at least
three independent experiments: bars indicate standard
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 13 of 18
redox collapse observed in postmitotic yeast cells. Cultivation under caloric restriction conditions
appears to delay the decrease in cellular NADPH levels, delays the redox collapse of the yeast
proteome, and extends lifespan.
In this study, we used a quantitative redox proteomic approach combined with metabolic measurements
to assess a time line of physiological redox events that occur in aging non-dividing cells, using
chronologically aging S. cerevisiae as a model system. We made the very surprising observation that
early during the chronological aging process and significantly before cell death sets in, yeast cells
undergo an abrupt loss in redox homeostasis as indicated by the massive oxidation of the large
majority of thiol-containing cytosolic, nuclear, and mitochondrial proteins. Importantly, this oxidation
event is significantly delayed by caloric restriction and even more so by a shift to hypometabolic
cultivation conditions, suggesting that maintenance of redox homeostasis might contribute to the
lifespan extending effects of these regimens. To begin to understand what physiological event(s)
trigger the observed redox collapse, we compared the kinetics of oxidation in almost 300 different
protein thiols. We noted that thiol oxidation occurs in at least two waves. The first wave, which
affects only a very small subset of identified thiol-containing proteins (<10%), hit cells cultivated in
standard media within 24–48 hr after reaching exponential growth. At this point, cells had stopped
dividing (Figure 1—figure supplement 1B), transitioned to respiratory growth, and NADPH
levels, which transiently increased during the diauxic shift, had started to decrease significantly
(Figure 6B). The second wave of oxidation, which occurred about 24 hr later, affected nearly
70% of the remaining identified yeast protein thiols (Figure 2). Yet as observed before, yeast
cells were able to maintain their energy resources (i.e., ATP levels) and to survive for several more
days after the collapse. Bioinformatic analysis revealed that many of the very early oxidation targets
are cysteines that form part of a C-X2/3-C motif (e.g., thioredoxin reductase, CCT4, CCT8, YdJ1,
RPL42, PAA1, MES1). This cysteine motif is often found in disulfide oxidoreductases, redox-sensitive
transcription factors, and many metal binding proteins, and confers considerable redox sensitivity to
proteins (Sanchez et al., 2008). Hence, this cysteine motif allows many of these proteins to form
transient disulfide bonds within the otherwise reducing environment of the cytosol. Based on the
popular free radical theory of aging, we first suspected that a sudden surge in or accumulation of
peroxide might be the cause of the early oxidation of these proteins. However, we found that only 5
of the 28 early oxidation targets were previously identified to contain peroxide-sensitive thiols (Table 1,
indicated with asterisk). Moreover, protein thiols that we had previously identified to be highly
peroxide-sensitive, such as the active site cysteines of GapDH or AHP1 (a thiol-peroxidase that
undergoes reversible disulfide bond formation upon peroxide detoxification) were not among the
early oxidation targets in yeast (Figure 1—Source data 1). These results suggested that elevated
peroxide production is unlikely the cause of the early oxidation event. Instead, we noted that the
early oxidation event is significantly preceded by a loss in cellular NADPH, the electron donor of the
NADPH-dependent thioredoxin system. Moreover, we found that under conditions of caloric
restriction, each of the individual processes was time-delayed by about 48 hr: NADPH decrease,
early protein (i.e., thioredoxin reductase) oxidation, and the collapse of the thiol redox proteome.
These findings raised the intriguing possibility that these processes are directly connected (Figure 7)
and that loss of NADPH might be the trigger for the observed redox collapse. Consistent with this
idea, analysis of the cellular GSH/GSSG ratio in chronologically aging yeast cells, which is dependent
on the NADPH-dependent glutathione reductase, revealed a pro-oxidizing shift in the GSH redox
potential that coincided with the decrease in cellular NADPH levels. As before, this pro-oxidizing
shift was significantly delayed in calorically restricted growth conditions (Figure 7). These findings
would explain how a reduction in caloric intake, which transiently increases cellular NADPH levels
(Figure 6B), is able to extend maintenance of the cellular redox balance and might contribute to
lifespan extension. It is noteworthy that similar pro-oxidizing shifts in thioredoxin and glutathione
systems have also been observed in aging rodents (Cho et al., 2003; Rohrbach et al., 2006; Rebrin
and Sohal, 2008), and might, at least in part, be explained by the observed decrease in cellular
NADPH levels in aging rats (Parihar et al., 2008). Consistent with our studies, caloric restriction at
least partially reversed the detected changes in redox status, shifted the glutathione pool to a more
reducing redox potential relative to cultures grown in 2% glucose, and increased cellular NADPH
levels (Someya et al., 2010). These results suggest that the observed decrease in cellular NADPH
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 14 of 18
levels and the concomitant increase in cellular redox potential is not just a yeast-specific event but
might be shared with other aging organisms as their metabolism changes. The fact that yeast cells
undergo the very same pattern of NADPH decrease, Trr1 oxidation and redox collapse (albeit
time-delayed) when cultivated in 2% glucose or in 0.5% glucose medium also argues against the
possibility that medium acidification, which has been discussed to accelerate chronological aging in
yeast, is a contributing factor to the observed effects, as medium acidification is severe in 2% glucose
yet insignificant in 0.5% glucose (Burtner et al., 2009).
It was intriguing to observe that early protein oxidation is, at least in its initial stage, a fully reversible
event in yeast. Moreover, we found that more than 80% of viable cells were recovered from day 3- and
day 4-old cultures despite an almost fully oxidized thiol proteome. It has been suggested that
oxidative thiol modifications, such as those detected by our OxICAT method, might serve a beneficial
purpose for cells by preventing irreversible thiol modifications that would ultimately lead to protein
degradation and potentially cell death (Gallogly and Mieyal, 2007). It is thus tempting to speculate
that the initially reversible thiol modifications that we observe in chronologically aging yeast cells
might in fact represent a ‘pro-active’ response of yeast cells to protect their proteins against irreversible
protein modifications and damage, and thereby extend lifespan. Quantitative studies conducted in
diamide-treated HeLa and HEK cells revealed that over 50% of protein thiols undergo reversible thiol
modifications in response to diamide stress, providing evidence that the combined redox proteome of
mammalian cells has a higher redox buffering capacity than glutathione (Hansen et al., 2009). While
the authors were unable to conclude whether this high redox buffering capacity of protein thiols is the
work of a few high abundance, highly cysteine-enriched proteins or a contribution of the majority of
thiol-containing proteins, our data suggest that the majority of yeast protein thiols have the capacity
to undergo reversible redox modifications and thereby serve as redox buffer. These results suggest
Figure 7. Timeline of redox events in chronologically aging yeast cells. The graphs shown provide a comparative
assessment of cell viability (based on data shown in Figure 1A), ATP levels (Figure 2B), NADPH levels (Figure 6B),
EGSH measurements (Figure 6A), and thiol oxidation states of representative early (i.e., PYC2) and general targets
(e.g., GapDH/TDH) (Table 1) during the chronological lifespan of yeast strain DBY746 under standard and caloric
restriction conditions. A colored scale for each assessed parameter is provided.
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 15 of 18
that chronological aging might represent a physiological stress condition that utilizes and stresses the
redox buffering capacity of the thiol proteome. At this point, we also cannot exclude that oxidation of
some key proteins might actually contribute to the potentially beneficial down-regulation of cellular
processes that would otherwise negatively affect yeast lifespan and shorten it even more. One such
example would be methionyl-tRNA synthetase (MES1), an enzyme involved in translational initiation
(Delarue, 1995) whose oxidation of Cys353 reaches over 65% at day 2 of cultivation in standard conditions
(Table 1). Intriguingly, Cys353 is part of a zinc finger-like CX2C-X9-CX2C motif whose substitution in the
E. coli homologue MetRS causes a strong decrease in enzyme activity (Fourmy et al., 1993).
Down-regulation of protein translation has been shown to contribute to increased oxidative stress
resistance and to extend lifespan in replicative aging yeast and other organisms (Steffen et al., 2008).
In summary, our results suggest that early changes in cellular NADPH levels might serve as a trigger
for the initial thioredoxin reductase oxidation, which subsequently leads to the redox collapse observed
in postmitotic yeast cells. Cultivation of yeast cells under caloric restriction conditions appears to delay
the decrease in cellular NADPH levels and hence delays the redox collapse of the yeast proteome. At
this point, it is unclear which event(s) cause the initial drop in intracellular NADPH levels that trigger the
redox collapse. Moreover, it remains to be determined whether this is a controlled pro-survival response
that extends an otherwise even shorter lifespan, or the first step on the final path to destruction.
Material and methods
Strains, cell growth and chronological lifespan measurements
S. cerevisiae strain EG103 (DBY746; MATα, leu2-3 112 his3Δ1 trp1-289a ura3-52) was cultivated in
synthetic complete dextrose (standard SCD) medium, which consists of 0.67% yeast nitrogen base
supplemented with complete amino acid mix (Guthrie, 2002) and 2% wt/vol glucose at 30°C. To
cultivate yeast under caloric restriction conditions, glucose concentration was decreased to 0.5% wt/vol.
Chronological lifespan was monitored as previously described (Fabrizio and Longo, 2007). Cell
aliquots were taken each day and viability was assessed using propidium iodide (PI) staining (Deere
et al., 1998). Viability is given as the percent of cells that are unstained by PI over the total number of
cells in the optic field. Deletion mutants of thioredoxin reductase 1 and 2 (TRR1 and TRR2) were
constructed in EG103 by using homologous recombination of a PCR product containing the ClonNAt
resistance marker (Goldstein and McCusker, 1999).
Differential thiol trapping of proteins during chronological lifespan and
EG103 cells were grown in standard or caloric restriction medium at 30°C with continuous shaking.
Once cells reached mid-logarithmic phase (OD600 of 0.5), the first cell aliquot was harvested
(corresponding to day 0). All further cell aliquots were harvested in 24-hr intervals (day 1, 2, etc.). For each
aliquot, 5 × 107 cells (total volume adjusted for changes in cell density) were harvested directly onto
10% (wt/vol) trichloroacetic acid (TCA) to stop all thiol-disulfide exchange reactions. TCA-precipitated
samples were incubated on ice for 30 min and the OxICAT thiol trapping protocol including mass
spectrometry and data analysis was conducted as described previously (Brandes et al., 2011).
The open-source software TIGR MultiExperimentViewer v4.4 (MEV; http://www.tm4.org/mev/) (Saeed
et al., 2006) and the algorithm k-means clustering with Euclidean distance (implemented in MEV)
were used for clustering analysis of peptides listed in Figure 1—Source data 1. Values missing in
those lists as a result of insufficient MS quantification were predicted with Coupled Two Way Clustering
(CTWC) (Weizmann Institute of Science, Israel; http://ctwc.weizmann.ac.il/) (Getz et al., 2000). The
prediction was based on five neighbors when more than 30% of the values were known.
Analysis of intracellular ATP concentrations
Intracellular ATP levels were determined as previously described (Bondar and Mead, 1974; Yang et al.,
2002). Results are expressed as mean ± standard deviation of three independent experiments.
Determination of intracellular glutathione concentrations
For determination of intracellular GSH and GSSG concentrations, 10 × 107 cells were harvested at the
indicated time points and the metabolites were measured after derivatization with iodoacetic acid and
Brandes et al. eLife 2013;2:e00306. DOI: 10.7554/eLife.00306 16 of 18
dinitrofluorobenzene followed by HPLC analysis (Garg et al., 2010). Redox potentials were calculated
using the Nernst equation: Eh = E0 + RT/2F ln[GSSG/(GSH)2] with E0 = −240 mV for the GSH/GSSG
Analysis of intracellular NADP(H) levels
Samples containing 1 × 107 cells were harvested by low speed centrifugation from chronologically
aging yeast cultures, washed with cold phosphate buffered saline (PBS), and resuspended to a final
OD600 of 10 using the extraction and lysis buffer provided by the fluorescent NADPH/NADP detection
kit from Cell Technology Inc. (Mountain View, CA). Cells were lysed with glass beads. Extraction and
detection of NADP+/NADPH was conducted according to the manufacturer’s protocol.
We thank Dr. James Bardwell for critically reading the manuscript. LC-MS/MS and MS analysis was
performed by the Michigan Proteome Consortium (www.proteomeconsortium.org), which was
supported in part by funds from the Michigan Life Sciences Corridor.
National Institutes of Health AG027349Ursula Jakob
National Institutes of HealthHL58984 Ruma Banerjee
National Institutes of Health AG000114 Heather Tienson
Human Frontier Science ProgramDana Reichmann
European Molecular Biology Organization Dana Reichmann
The funders had no role in study design, data collection and interpretation, or the decision
to submit the work for publication.
NB, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article; HT,
Acquisition of data, Analysis and interpretation of data, Drafting or revising the article; AL, Acquisition
of data; VV, Acquisition of data; DR, Analysis and interpretation of data, Drafting or revising the
article; RB, Analysis and interpretation of data; UJ, Conception and design, Analysis and interpretation
of data, Drafting or revising the article
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